Abstract One of the major challenges for effective agricultural activity monitoring systems is defining robust indicators of spatial and temporal variability for the main risk factors associated with crop production. In this context, this study aimed to analyze the potential of the Temperature-Vegetation Dryness Index (TVDI), obtained by terrestrial and orbital sensors from soybean production areas in southern Brazil, in generating spatial and temporal patterns of the main risk factor, surface moisture, to be incorporated in operational agricultural monitoring systems. For this purpose, MODIS Terra and Landsat-8 OLI/TIRS sensor images were used, as well as data from surface positioned sensors to serve as a reference. The study area encompassed one soybean crop area, soybean mapped crop areas near the experimental area, and the municipality of Carazinho-RS. The experimental area was analyzed during the soybean growing season. As the TVDI data estimated by OLI/TIRS and MODIS sensors were coherent and robust, both sensors can be used in conjunction for agricultural risk monitoring. Its main features are continuous monitoring of large production regions by TVDIMODIS and spatial distribution detailing by TVDIOLI/TIRS in critical periods to water deficit.

Resumo Um dos importantes desafios para construção de sistemas eficazes de monitoramento agrícola é a definição de indicadores que representem a variabilidade espacial e temporal dos principais fatores de risco associados à produção. Neste contexto, se analisou a potencialidade de uso do TVDI (Temperature-Vegetation Dryness Index), obtido a partir dos sensores terrestres e orbitais em áreas de produção de soja no sul do Brasil, na geração dos padrões espaciais e temporais do principal fator de risco, a umidade da superfície, visando sua incorporação em sistemas operacionais de monitoramento agrícola. Utilizou-se imagens dos sensores MODIS Terra e OLI/TIRS Landsat 8, e dados de sensores posicionados na superfície que serviram como referência. A área de estudo abrangeu lavoura de soja, onde foi conduzido o experimento, lavouras de soja próximas e o município de Carazinho/RS. O período de análise foi o período de cultivo da soja. Dada a coerência e robustez do TVDI estimado pelos sensores orbitais, verificou-se que é possível o uso conjugado destes sensores em sistema de monitoramento de risco agrícola. A principal característica é o acompanhamento contínuo da umidade em amplas regiões agrícolas usando TVDIMODIS e detalhamento da distribuição espacial da umidade da superfície com TVDIOLI/TIRS nos períodos críticos à deficiência hídrica.

Resumo O objetivo deste trabalho foi avaliar o uso dos dados de umidade da superfície gerados pelo índice “temperature-vegetation dryness index” (TVDI), obtido de sensores posicionados na superfície de uma área agrícola de soja (Glycine max). Os limites seco e úmido do índice foram obtidos com uso de imagens Landsat-8 que abrangem a região em torno da lavoura. Para avaliar a qualidade e a coerência do TVDI, foi realizada análise de correlação entre o TVDI, o “normalized difference vegetation index” (NDVI), a temperatura da superfície (TS), e as variáveis usualmente utilizadas para expressar a umidade da superfície. O TVDI mostrou correlação significativa com umidade do solo, armazenamento de água no solo, deficit hídrico, evapotranspiração real e relação evapotranspiração real/evapotranspiração potencial. O deslocamento dos dados radiométricos medidos na superfície (NDVI e TS) dentro do triângulo evaporativo, ajustado com dados orbitais, descreve de forma consistente a variabilidade das condições hídricas no período de estudo, sendo uma ferramenta para apoio à tomada de decisões no manejo de culturas.

Abstract The objective of this work was to evaluate the use of the surface moisture data generated by the temperature-vegetation dryness index (TVDI), obtained from sensors positioned on the surface of a soybean (Glycine max) agricultural field. The dry and wet limits of the index were obtained using Landsat-8 images covering the region around the crop. To assess the quality and consistency of the TVDI, a correlation analysis was carried out between the TVDI, the normalized difference vegetation index (NDVI), surface temperature (TS), and the variables that are usually used to express surface moisture. The TVDI showed a significant correlation with soil moisture, water storage in the soil, water deficit, real evapotranspiration, and the real evapotranspiration/potential evapotranspiration ratio. The displacement of radiometric data measured on the surface (NDVI and TS) within the evaporative triangle, adjusted with orbital data, consistently describes the variability of water conditions during the study period, being a tool to support decision-making in crop management.

Resumo O objetivo do estudo foi analisar a variabilidade no TVDI (Temperature-Vegetation Dryness Index) obtido de sensores orbitais com resoluções distintas, em região agrícola no sul do Brasil. Utilizou-se três imagens OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) do satélite Landsat 8, e 12 imagens MODIS (Moderate Resolution Imaging Spectroradiometer) do satélite Terra. Dados coletados em campo serviram como base para classificação de imagem OLI/TIRS e mapeamento de áreas de arroz, soja, campos naturais, mata ciliar e solo exposto. O TVDI foi obtido por duas parametrizações em períodos distintos, utilizando as dispersões entre Temperatura de Superfície (TS) e NDVI (Normalized Difference Vegetation Index). O TVDI obtido para ambos sensores apresentou padrão similar possibilitando diferenciar os alvos. Na média de todas as datas e classes, o TVDI obtido das imagens MODIS foi superior em 0,128 unidades ao TVDI obtido com o OLI/TIRS. Quando utilizado OLI/TIRS há um melhor detalhamento espacial das condições hídricas, mas com menor repetição ao longo da safra; já utilizando o TVDI-MODIS é possível monitorar as condições hídricas em escala regional, com menor detalhamento espacial, mas com maior repetitividade no tempo. O TVDI estimado pelos sensores OLI/TIRS e MODIS, pode ser utilizado de forma conjunta, trazendo informações complementares.

Abstract The aim of the study was to analyze the variability in the TVDI (Temperature-Vegetation Dryness Index) obtained from orbital sensors with distinct resolution in an agricultural region in southern Brazil. Three images of the Landsat 8 satellite OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) and 12 of Terra’s MODIS (Moderate Resolution Imaging Spectroradiometer), were used. Data collected in the field served as a basis for OLI/TIRS image classification and mapping of rice, soybean, grasslands, gallery forest and bare soil areas. The TVDI obtained by two parameterizations at different periods was evaluated, using the dispersions between Surface Temperature (TS) and NDVI (Normalized Difference Vegetation Index). The TVDI obtained for both sensors presented a similar pattern allowing differentiation of the targets. The average of all dates and classes, TVDI obtained from MODIS was 0.128 units higher than the obtained with the OLI/TIRS. When used OLI/TIRS there is a better detail in the representation of the moisture, but with less repetition throughout the crop cycle. Using TVDI-MODIS, it is possible to monitor moisture conditions on a regional scale, with less spatial detail, but in a continuous way over time. The TVDI estimated by the OLI/TIRS and MODIS can be used together, providing complementary information.

ABSTRACT: Soybean crops occupy most areas in Rio Grande do Sul State and are highly dependent on rainfall since most of them are non-irrigated. Rainfall during the harvest period is often insufficient to meet the water demand, making water indicators an important tool for the crops. This study compared two approaches in the parameterization process of TVDI (Temperature-Vegetation Dryness Index) in a subtropical climate region of Brazil. The process used Moderate Resolution Imaging Spectroradiometer (MODIS) images of the surface temperature (TS) and Normalized Difference Vegetation Index (NDVI), with spatial resolutions of 1,000 m and periods of 8-16 d, respectively. The evaporative triangles for the TS/NDVI scatter plots were built either for each image (scene-specific parameterization) or for all images at once (crop-type parameterization). The rainfall data were obtained from meteorological stations located in the study site and the analysis period comprised two contrasting harvests regarding soybean yield (most important crop in the region). The scene-specific parameterization allowed to analyze water status in the study site by inspecting the wet and dry edge of each image and identifying the areas of stress in each one. TVDI crop parameterization showed that the model was able to determine the time and frequency of water stress events during the crop-seasons. TVDI crop-parameterization, therefore, is more consistent for crop monitoring and forecasting purposes.

ABSTRACT The most southern Brazilian state, Rio Grande do Sul, is characterized by high crop yield and is, currently, the third leading soybean producer in the country. Therefore, agriculture is very important to the economy of the region. Because agriculture is highly dependent on variable weather parameters, the present study aimed to test the Temperature-Vegetation Dryness Index (TVDI) as a regional indicator of water status under the climate and soybean crop management conditions that predominate in northwestern Rio Grande do Sul. For this, soybean crop seasons with contrasting yields were selected: 2004 – 2005 (yield 0.5 t∙ha–1) and 2009 – 2010 (2.7 t∙ha–1). TVDI was obtained from the surface temperature (TS) and Normalized Difference Vegetation Index (NDVI) images available from MODIS products, which were correlated to obtain a triangular scatter plot. Rainfall data from surface weather stations were also used. The results showed that the pattern of the TVDI is associated with rainfall variability. However, as the TVDI is based on normalization of the wet and dry edges of each image individually, the comparison of TVDI values across different images is challenging. This deficiency can be mitigated by analysis of the parameters used to derive the index. Therefore, both the TVDI and the “b” and TSmin parameters used to derive it can elucidate the patterns of crop response to water availability.